MétaCan
Menu
Back to cohort
Record W1865350477 · doi:10.3109/00207454.2015.1051046

Reduced plasma taurine level in Parkinson's disease: association with motor severity and levodopa treatment

2015· article· en· W1865350477 on OpenAlexaboutno aff
Li Zhang, Yongsheng Yuan, Qing Tong, Siming Jiang, Qinrong Xu, Jian Ding, Lian Zhang, Rui Zhang, Kezhong Zhang

Bibliographic record

VenueInternational Journal of Neuroscience · 2015
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsTaurineLevodopaInternal medicineParkinson's diseaseEndocrinologyMedicinePsychologyDiseaseGastroenterologyChemistryBiochemistry

Abstract

fetched live from OpenAlex

PURPOSE: This study aimed to evaluate the level of taurine in plasma, and its association with the severity of motor and non-motor symptoms (NMS) and chronic levodopa treatment in Parkinson's disease (PD). PATIENTS AND METHODS: Plasma taurine level was measured in treated PD (tPD), untreated PD (ntPD) and control groups. Motor symptoms and NMS were assessed using the Unified Parkinson's Disease Rating Scale, the short form of the McGill Pain Questionnaire, the Hamilton Depression Scale, the Scale for Outcomes in Parkinson's disease for Autonomic Symptoms and the Pittsburgh Sleep Quality Index. Longtime exposure to levodopa was indicated by its approximate cumulative dosage. RESULTS: The plasma taurine levels of PD patients were decreased when compared with controls and negatively associated with motor severity but not NMS. Moreover, tPD patients exhibited lower levels of plasma taurine than ntPD patients. Interestingly, plasma taurine levels negatively correlated with cumulative levodopa dosage in tPD. After controlling for potential confounders, the association between taurine and levodopa remained significant. CONCLUSION: Our study supports that taurine may play important roles in the pathophysiology of PD and the disturbances caused by chronic levodopa administration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.305
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations36
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of NeuroscienceSame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207